IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i5p3056-d764790.html
   My bibliography  Save this article

Association of Preterm Birth with Inflammatory Bowel Disease and Salivary Gland Disease: Machine Learning Analysis Using National Health Insurance Data

Author

Listed:
  • Kwang-Sig Lee

    (AI Center, Korea University Anam Hospital, Seoul 02841, Korea
    These authors contributed equally to this work.)

  • Eun Sun Kim

    (Department of Gastroenterology, Korea University Anam Hospital, Seoul 02841, Korea
    These authors contributed equally to this work.)

  • In-Seok Song

    (Department of Oral and Maxillofacial Surgery, Korea University Anam Hospital, Seoul 02841, Korea)

  • Hae-In Kim

    (AI Center, Korea University Anam Hospital, Seoul 02841, Korea
    School of Industrial Management Engineering, Korea University, Seoul 02841, Korea
    Department of Obstetrics and Gynecology, Korea University Anam Hospital, Seoul 02841, Korea)

  • Ki Hoon Ahn

    (Department of Obstetrics and Gynecology, Korea University Anam Hospital, Seoul 02841, Korea)

Abstract

This study employs machine learning and population data for testing the associations of preterm birth with inflammatory bowel disease (IBD), salivary gland disease, socioeconomic status and medication history, including proton pump inhibitors. The source of population-based retrospective cohort data was the Korea National Health Insurance Service claims data for all women aged 25–40 years and who experience their first childbirths as singleton pregnancy during 2015 to 2017 (402,092 women). These participants were divided into the Ulcerative Colitis (UC) Group (1782 women), the Crohn Group (1954 women) and the Non-IBD Group (398,219 women). For each group, the dependent variable was preterm birth during 2015–2017, and 51 independent variables were included. Random forest variable importance was employed for investigating the main factors of preterm birth and testing its associations with salivary gland disease, socioeconomic status and medication history for each group. The proportion of preterm birth was higher for the UC Group and the Non-IBD Group than for the Crohn Group: 7.86%, 7.17% vs. 6.76%. Based on random forest variable importance, salivary gland disease was a top 10 determinant for the prediction of preterm birth for the UC Group, but this was not the case for the Crohn Group or the Non-IBD Group. The top 5 variables of preterm birth for the UC Group during 2015–2017 were socioeconomic status (8.58), age (8.00), proton pump inhibitors (2.35), progesterone (2.13) and salivary gland disease in 2014 (1.72). In conclusion, preterm birth has strong associations with ulcerative colitis, salivary gland disease, socioeconomic status and medication history including proton pump inhibitors.

Suggested Citation

  • Kwang-Sig Lee & Eun Sun Kim & In-Seok Song & Hae-In Kim & Ki Hoon Ahn, 2022. "Association of Preterm Birth with Inflammatory Bowel Disease and Salivary Gland Disease: Machine Learning Analysis Using National Health Insurance Data," IJERPH, MDPI, vol. 19(5), pages 1-11, March.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:5:p:3056-:d:764790
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/5/3056/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/5/3056/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:5:p:3056-:d:764790. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.